Question 68 - DEA-C01 discussion

In a typical table, the data is stored in the database; however, in an external table, the data is stored in files in an external stage. External tables store file-level metadata about the data files, such as the filename, a version identifier and related properties. This enables querying data stored in files in an external stage as if it were inside a database. External tables can access data stored in any format supported by COPY INTO <table> statements.

External tables are read-only, therefore no DML operations can be performed on them; however, external tables can be used for query and join operations. Views can be created against external tables.

Querying data stored external to the database is likely to be slower than querying native database tables; however, materialized views based on external tables can improve query performance.

Creating External tables enable user for querying existing data stored in external cloud storage for analysis without first loading it into Snowflake. The source of truth for the data remains in the external cloud storage. Data sets materialized in Snowflake via materialized views are read-only.

This solution is especially beneficial to accounts that have a large amount of data stored in external cloud storage and only want to query a portion of the data; for example, the most recent data. Users can create materialized views on subsets of this data for improved query performance.